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Guidance in this section describes conventions for the population of tabulation records and variables. Conventions in this section are both general and provided by general observation class. When conventions are applicable to TIG Nonclinical and Product Impact on Individual Health use cases, this is denoted in the Implementation column,


The following are general conventions for variable population:

NumVariable PopulationImplementation
1Text Strings Greater Than 200 Characters

When text strings greater than 200 characters are collected, the following conventions for general observation class variables and SUPP-- datasets will be adhered to:

  • The first 200 characters of text should be stored in the parent domain variable and each additional 200 characters of text should be stored in a record in the SUPP-- dataset.
    • When splitting a text string into several SUPP-- records, the text should be split between words to improve readability.
    • The value of the first QNAM representing text over 200 characters will be the original domain variable name without any numeric suffix. 
    • The values for subsequent QNAMs will be sequential variable names, formed by appending a 1-digit integer, beginning with 1, to the original domain variable name. In cases where the standard domain variable name is already 8 characters in length, applicants will replace the last character with a digit when creating values for QNAM.
      • e.g., For Other Action Taken in Adverse Events (AEACNOTH), values for QNAM for the SUPPAE records would have the values AEACNOT1, AEACNOT2, and so on.
    • The value for QLABEL should be the original domain variable label for all QNAM values.
2"Yes", "No", Values
  • For variables where the response is "Yes" or "No", both "Y" and "N" will be   
  • Variables where the response is "Yes" or "No" ("Y" or "N") should normally be populated for both "Y" and "N" responses. This eliminates confusion regarding whether a blank response indicates "N" or is a missing value. However, some variables are collected or derived in a manner that allows only 1 response, such as when a single checkbox indicates "Yes". In situations such as these, where it is unambiguous to populate only the response of interest, it is permissible to populate only 1 value ("Y" or "N") and leave the alternate value blank. An example of when it would be acceptable to use only a value of "Y" would be for Last Observation Before Exposure Flag (--LOBXFL) variables, where "N" is not necessary to indicate that a value is not the last observation before exposure.
3

--FOCID

Often, a specific part of a subject or specimen is identified as a study-specific point of interest (e.g., injection site, biopsy site, treated site, region of the body) and is commonly referenced in data collections and tabulations.

The FOCID variable enables representation of this concept, and is available within all general observation classes. When used, the variable serves as a cross-domain identifier for the study-specific focus of interest; any records relating to the same focus would have the same FOCID value. When populated, it is usually part of the natural key for the domain, providing a level of granularity that would otherwise not be available through the other variables. This is especially true when the foci are all within the same area on the subject.

The following examples demonstrate records from various domains that tie to study-specific foci (i.e., injection site 1 and injection site 2) as identified in the protocol. In each case, the FOCID variable is populated identically across domains for the same focus. Note that, in this example, many variables have been omitted due to space considerations.

At each of the 2 injection sites, subject 12345001 received a different treatment (Exposure domain).

4

--SEQ, --RECID

Variables --SEQ and --RECID are populated to explicitly identify domain records in different ways. Differences in variable population are described below.

--SEQ--RECID
Values uniquely identify records for subjects within a domain.Values uniquely identify records within a domain.

The relationship between records and values is not one-to-one.

  • Values may change between versions of datasets.
  • When a record is deleted, the value for the record may be reused to identify another record.

There is a one-to-one relationship between records and values.

  • Values for records do not change between versions of datasets even when content is modified. 
  • When a record is deleted, the value for the record will not be reused to identify another record.
Variable is numeric with numeric values.Variable is character with numeric, character, or alphanumeric values.
Conventions for establishing and maintaining values are applicant-defined. Values may or may not be sequential depending on data processes and sources.



5--GRPID
  • The value of --GRPID is generally assigned during or after data collection at the discretion of the applicant.
6

--REFID

  • Values for --REFID are sponsor-defined and can be any alphanumeric strings the sponsor chooses, consistent with their internal practices.
7--CAT, --SCAT
  • Values for --CAT and/or--SCAT are known (identified) about the data before it is collected.
  • Variable --SCAT will be populated only when there is a value in variable --CAT.
8--STAT
  • In general observation class domains, --STAT will be populated with "NOT DONE" when data are not collected for the topic of the observation.

The following are conventions for variable population in Interventions and Events class domains. 

NumVariable PopulationImplementation
1

Prespecified interventions and events (--PRESP, --OCCUR, --STAT, REASND)

Product Impact on Individual Health Only:

Interventions (e.g., concomitant medications) and events (e.g., medical history) can be collected as responses to a prespecified list of treatments or terms. In such cases:

  • --PRESP represents when topic variable values, specific interventions (--TRT) or events (–TERM), were prespecified at the time of data collection. Values will be "Y" (for "Yes") or a null value.
  • --OCCUR represents whether prespecified interventions or events occurred or did not occur. Values will be populated for prespecified interventions and events only populated will be "Y" and "N" (for "Yes" and "No"). When an intervention or event is not prespecified, the value of --OCCUR will be null. 
  • --STAT and --REASND can be used to provide information about prespecified interventions and events for which there is no response (e.g., investigator forgot to ask). In such cases the value of --STAT will be "NOT DONE" and the value of --REASND will be the reason when collected.

The following table shows the population of --PRESP, --OCCUR, --STAT, and --REASND for different data collection scenarios.

Collection Scenario--PRESP Value--OCCUR Value--STAT Value--REASND Value
An intervention or event was prespecified at the time of collection and occurred.YY

An intervention or event was prespecified at the time of collection and did not occur.YN

An intervention or event was prespecified at the time of collection with no response and no reason collected.Y
NOT DONE
An intervention or event was prespecified at the time of collection with no response and reason collected.Y
NOT DONEForgot to ask.
A spontaneously reported intervention or event was collected.



2Reason for an Action or Activity
  • For Interventions class domains, --INDC will represent the medical condition for which the intervention was given and --ADJ will represent the reason for an adjustment to exposure, when collected.
  • For Events class domains, reasons for performing an activity will be represented using nonstandard variable(s) in the SUPP-- dataset with QNAM = --REAS. 

The following are conventions for variable population in Findings class domains. 

NumRecord and Variable PopulationImplementation
1Result Precision
  • For numeric non-derived data, --ORRES will represent results to precision collected. Precision will not be artificially changed due to computer storage considerations.
  • For numeric derived data, --ORRES and --STRESC will represent the correct number of significant figures based upon the calculation used to derive the value. Trailing zeroes will be retained when significant.
2Standardized Units

Applicants may standardize units within a study for a given test per scientific and regulatory requirements. Standardization of units is recommended when data for the same test are collected via different sources using different units. In such cases, --ORRESU will represent the collected unit and --STRESU will represent the standardized unit.

3Original and Standardized Results (--ORRES, --ORRESU, --STRESC, --STRESU, --STRESN) 

If supplemental free text is collected for a result via CRF, then refer to Section x.x, Free Text from Case Report Forms (CRFs). For responses collected via QRS instruments, refer to QS domain assumptions.   

For all other results:

  • --ORRES will be populated with the result of the measurement or finding as originally collected or received, using controlled terminology when applicable.  
    • When applicable, the unit associated the value of --ORRES will be populated in --ORRESU, using controlled terminology. 
  • Values will be populated in --STRESC when --ORRES is populated. The value of --STRESC will be:
    • Derived by the conversion of numeric values in --ORRES to numeric values with standard units. Standard units will be represented in --STRESU using controlled terminology.
      • Numeric --ORRES values with characters attached (e.g., a greater than (>) or less than (<) sign) will be converted to standard units and the value of --STRESC will maintain the attached character (e.g., >10,000, <1). 
    • The assigned of the value of --ORRES. 
      • For nonclinical studies, in the Macroscopic and Microscopic Findings (MA/MI) domains, --ORRES may contain a finding with multiple concatenated modifiers. In this case, --STRESC would represent only the finding without the modifiers. 
  • Numeric values represented in --STRESC will be assigned to --STRESN. If --STRESC is a character value, then, --STRESN will be null. 
    • Numeric values with attached characters (e.g., >10,000, <1) are considered to be character results and will not be populated in --STRESN.
4Reason Test Performed (--REASPF)

--REASPF will represent the reason a test was performed, if collected.

5Tests Not Done

When an entire examination (e.g., Laboratory Test Results (LB)), a group of tests (e.g., hematology or urinalysis), or an individual test (e.g., glucose) is not done for a USUBJID, POOLID, or SPTOBID and this information is explicitly captured with or without the reason for not collecting the information, record(s) can be created in the dataset to represent these data.

In such cases, applicants may include:

  • Individual records for each test not done for each subject or pool; or
  • One record for each subject or pool for a group of tests that were not done. In such cases:
    • The paired values of --TESTCD and --TEST will represent a general description of testing in scope for the domain and will be used for all groupings of not done tests within the domain.  
      • --TESTCD will be the domain code concatenated with the word "ALL".
      • --TEST will be the domain description per controlled terminology.
    • --CAT will represent the group of tests not done.
    • --ORRES will be null.
    • --STAT will be "NOT DONE".
    • --REASND will be the reason the group of tests was not done, if collected.

For example, if a group of hematology or urinalysis tests represented in the LB domain are not done for a subject, then:

USUBJIDLBTESTCDLBTESTLBCATLBORRESLBSTATLBREASND
ABC-001LBALLLaboratory Test ResultsHEMATOLOGY
NOT DONE
ABC-001LBALLLaboratory Test ResultsURINALYSIS
NOT DONENo urine specimen present
6Biological Significance 

Nonclinical Only:

  • For assessments of biological significance when the overall interpretation is a record in the domain, use the supplemental qualifier (SUPP--) record (with QNAM = --BIOSIG) linked to the record that contains the overall interpretation or a particular result.
    • An example would be a QNAM value of LBBIOSIG in SUPPLB with a value of "Y", indicating that a lab result for albumin of 30 mg/mL was biologically significant.
  • Biological significance is not the same as the concepts of normal and abnormal, which are generally represented in --ORRES.
7Clinical Significance

Product Impact on Individual Health Only:

  • For assessments of clinical significance when the overall interpretation is a record in the domain, use the --CLSIG (Clinically Significant) variable on the record that contains the overall interpretation or a particular result.
    • For example, EGCLSIG = "Y" indicates that an ECG result of "ATRIAL FIBRILLATION" was clinically significant.
  • Clinical significance is not the same as the concepts of normal and abnormal and lab values out of normal range which are generally submitted in --ORRES and normal range/indicator variables respectively.
8Records for Derived Results

Nonclinical:

  • When there is a need to derive results based on collected values in --ORRES (e.g., means or ratios base on collected values), a new record for the derived result will be created in the dataset. In such cases, --DRVFL will be populated with "Y" in the derived record.  --GRPID may be used to explicitly define the relationship between a derived record and the records from which it was derived. This practice would be especially important in the case of multiple derived records in a domain for the same subject (e.g., 2 baseline averages). 
    • For example, a mean systolic blood pressure derived from collected systolic blood pressure would be represented in the following way:
CVGRPIDCVTESTCVORRESCVDRFLCVDTC
1Systolic Blood Pressure154
2023-04-02T09:52
1Systolic Blood Pressure149
2023-04-02T09:54
1Systolic Blood Pressure153
2023-04-02T09:55
1Systolic Blood Pressure152Y2023-04-02


Product Impact on Individual Health:

  • Derived records will only be created for QRS domains as applicable. Refer to Section x.x, Questionnaires, Ratings, and Scales (QRS).
  • Otherwise, records for derived results will not be created. When needed such results will be derived as part of analysis.
9Dates Collected as Results
  • When appropriate, dates that are collected results will be represented as results in variable --ORRES.
  • Prior to representing a date as a result, confirm the date is actually a finding for an observation and not the timing of an observation.

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